Positive relationship between risk-taking behaviour and aggression in subordinate but not dominant males of a Cuban poeciliid fish
Bibliographic record
Abstract
Studies of integrated phenotypes sometimes reveal correlations between mating effort, favoured by sexual selection, and risk-taking, favoured by survival selection. We usedGirardinus metallicusto examine the relationship between rank order of mating effort and risk-taking. We measured risk-taking in a novel environment containing a predator. We then paired males, using aggression to assign dominant or subordinate status, and examined mating behaviour. Dominant males showed higher mating effort, but did not exhibit any relationship between risk-taking and mating effort. Subordinate males exhibited a cross-context correlation, as males were either more willing to take risks and aggressive or more hesitant to take risks and nonaggressive. Less risk-averse, aggressive subordinate males may gain fitness advantages in a more realistic dominance hierarchy, despite being outranked by the rival with which they were paired in our study. Results highlight intraspecific variation in behavioural correlations and the importance of social environment in shaping integrated phenotypes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".